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Diffusion Tensor Imaging Analysis of Regional Whiter Matter Changes

along the Cingulum in Mild Cognitive Impairment

Xuwei Liang†, Ning Kang†, Stephen E. Rose††, Jonathan B. Chalk††, Jun Zhang†

† Laboratory for Computational Medical Imaging & Data Analysis,

Department of Computer Science, University of Kentucky,

Lexington, KY 40506-0046, USA

†† Centre for Magnetic Resonance, University of Queensland,

Brisbane, QLD, 4072, Australia

Technical Report No. 489-07, Department of Computer Science, University of

Kentucky, Lexington, KY, 2007

Address for correspondence:

Dr. Jun Zhang

Laboratory for Computational Medical Imaging & Data Analysis,

Department of Computer Science, University of Kentucky,

Lexington, KY 40506-0046, USA

jzhang@cs.uky.edu

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Abstract

Diffusion tensor imaging (DTI) based tractography enables selective reconstruction of

specific white matter (WM) pathways. The cingulum tracts, connecting hippocampal,

thalamic and association cortices, are suspected to be involved in the episodic memory

impairment in mild cognitive impairment (MCI). We investigate the local micro structural

WM changes along the cingulum paths that could not be studied effectively due to its

curvilinear feature in the posterior and anterior regions, which causes significant difficulty in

defining the regions of interest and in comparing diffusion properties across individual

subjects in three dimensional (3D) brain images. We develop a new analysis technique to

define the complex 3D regions of interest, reconstruct the entire cingulum tracts, and measure

the regional micro structural WM alternations along the major fiber bundles. Our approach is

based on DTI tractography and geodesic path mapping, which allows cross-subject

evaluation of diffusion properties along the cingulum by parameterizing the space of

reconstructed pathways as a function of geodesic distance. Assessment of the technique by

comparing 17 MCI participants and 17 controls reveals specific anatomical locations along

the left cingulum paths with significantly reduced fractional anisotropy value in the MCI

subjects. The results show that this analysis technique is promising and may provide a

sensitive approach to determining the integrity of WM tracts for complex regions of interest

in the brain.

Key Words: Mild cognitive impairment, cingulum, diffusion tensor imaging, tractography,

geodesic distance.

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Introduction

A subtype of mild cognitive impairment (MCI), namely amnestic MCI, is presumed to

represent a typical prodrome of dementia in Alzheimer’s disease (AD) [1]. Recently it has

been hypothesized that episodic memory impairment in AD most likely involves dysfunction

of an integrated network involving the medial temporal lobe, thalamus and posterior

cingulum, with the posterior cingulum potentially of greatest importance in generating this

cognitive deficit [2]. As the cingulum connects hippocampal, thalamic and association

cortices, investigating the local changes within this important white matter (WM) pathway

has attracted significant attention [6, 7, 8].

Diffusion tensor imaging (DTI) based tractography enables selective reconstruction of

specific WM pathways. The fractional anisotropy (FA) value, a quantitative measure of the

degree of anisotropy, can be used to probe the integrity of brain WM [3]. The mean

diffusivity (MD) value is a quantitative measure of the bulk mean motion of water considered

in all directions and is used to study pathological changes in cerebral tissue [4]. DTI permits

the 3D visualization of individual WM tracts or even fiber track networks in the brain. Such

an approach has been successfully employed to evaluate FA value changes in the cingulum

tracts in AD [5].

Region-of-interest (ROI) [6] and voxel based morphometric (VBM) [7, 8] analyses have

shown reduced FA values within the dorsal posterior regions of the cingulum bundles in

subjects with MCI. But there are known limitations with these approaches [9]. Alternative

strategies involving the analysis of diffusivity measures along computed fiber tracts using

scale-invariant parameterization were proposed [10,11]. Due to the curved spatial nature of

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the cingulum tracts, it is difficult to use existing techniques to explore the regional WM

alternations effectively along the posterior and anterior cingulum tracts.

The objective of this study is to develop an effective technique to define the complex 3D

regions of interest for cingulum, and measure the regional micro structural WM changes

along its major fiber bundles. Our analysis approach is based on geodesic path mapping,

which allows direct cross-subject evaluation of diffusion properties along the

tractography-extracted fibers by parameterizing the space of the computed pathways as a

function of the geodesic distance. More specifically, we constructed both the left and right

cingulum bundle masks from a tensor averaged image of all subjects in the study and then

applied the masks to each individual subject. FA value indexed color maps were used to

validate the masks. Positions of the masks when they were overlapped in an individual color

map were adjusted if necessary. Geodesic paths were constructed for the fiber tracts based on

the MD and FA measures. To investigate regional micro structural changes, significant

differences in these diffusivity measures were quantitatively analyzed along the entire

geodesic path lengths in a contiguous manner. The possible impact on the analysis results

caused by the ROIs of different size was evaluated as well.

Methods

Patients and DTI Data Acquisition

Seventeen healthy elderly adults and seventeen MCI participants took part in the study.

Patient information and the collection pocesdure of the DTI data are detailed in [8]. In

particular, a 1.5T Siemens Sonata scanner was used for collecting the raw images. The

imaging parameters were 48 axial slices, FOV = 230 mm, TR = 6000 ms, TE = 106 ms, 2.5

5

mm slice thickness with 0.25 mm gap, acquisition matrix 128x128, and 60 images were

acquired at each location consisting of 16 with low diffusion weighting (b=0) and 44

diffusion-weighted images with encoded gradient vectors (b=1100 s/mm2). The

reconstructed matrix was 256x256, with a resulting resolution of 0.898x0.898x2.75 mm3.

Cingulum Tractography Mask

The cingulum is only about one voxel size (less than 3mm) thick in which situation the

extracted fiber is easy to be distorted by noise and partial volume effects, in addition to its

volume loss and FA value degradation. It is difficult to track anatomically valid cingulum

bundles for all MCI participants by directly applying the standard tractography algorithms.

To facilitate group comparison of diffusion properties, we generated a tensor averaged image

from all of the 34 DTI data. The tensor averaged image has much less noise and can be used

to reconstruct more anatomically representative fiber tracts than that of the individual

subjects. The left and right cingulum bundle masks were extracted from this tensor averaged

DTI data.

A set of DTI data processing and fiber tracking algorithms have been proposed by different

groups [16, 17, 25]. In this study, we integrated these well-established mehods and

interactive virtualization tools into a home-made software package. In fiber tracking, we

employed the backward streamline tractography technology proposed by Mori et al. [ 18] and

Conturo et al. [19]. Thresholds for the FA value and the curviture for terminating the fiber

tracking process were set to be 0.15 and 30 degree, respectively. The extracted fiber bundles

were validated and trimmed in the FA value indexed color map. We then applied these

cingulum tract masks to all the 17 controls and 17 MCI subjects to assess the DTI

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measurements. Figure 1 illustrates the right cingulum bundle mask overlapped on a tensor

averaged color map. (a ) and (b) are in sagittal and axial views, respectively. (c) shows the

voxels passed through by the fiber mask in a sagittal view. These voxels can be used to

explore the FA and MD value differences in the voxel level detail if necessary. This point will

be revisited later in the Result Section. The ROI used to generate the fiber tracts is shown in

blue. In this study, we employed FA value indexed color maps to facilitate the placement of

ROI and to validate the cingulum bundles [6].

Figure 1 The right cingulum tract mask is overlapped on an FA value indexed color map.

Left and top right subfigures are the mask in axial and sagittal views respectively. The ROI is

in blue and is the starting point of the geodesic mapping. The bottom right subfigure shows

the voxels passed through by the fiber mask in a sagittal view rendered in frames. The color of

a voxel indicates the FA value at that voxel. FA value goes from low to high according to the

color scheme from blue to green.

Mapping onto Geodesic Paths

To accommodate the highly curved nature and evaluate the integrity of the cingulum tracts in

MCIs, diffusion properties were statistically analyzed along fiber bundles mapped as

geodesic paths [20]. Fiber tract masks extracted from the averaged tensor image were stored

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as sets of curvilinear polylines parameterized by arc-length. The diffusion properties (the MD

and FA values) were carried as attributes on each node in the curvilinear structure. The

geodesic path for a fiber bundle (a set of individual pathways) originating from a predefined

starting ROI was calculated by averaging the attribute values across each tract with a polyline

represented as a function of geodesic distance from the starting ROI.

Let iψ be attribute values on the i-th fiber pathway and dj the geodesic distance of the j-th

node in the curvilinear structure. Then the geodesic path for a fiber bundle with average

attribute ψ is computed as

ψ (d j ) = 1n

ψ i (d j ),i=1

n

∑ j = 1,L, m.

We adopted the same scheme of coalescing fiber bundles among different subjects for the

purpose of group comparisons, with the assumption that the applied cingulum bundle masks

present comparable anatomical structures. In order to ensure the comparability of fiber tract

anatomy across individual tensor datasets, all images of the participants were registered to the

same standardized reference space before the tractography algorithm was applied. This was

achieved by non-linearly registering all subjects’ b=0 images (essentially the T2-weighted

MRI) to the MNI (Montreal Neurological Institute) template known as the ICBM152 [21]. A

hierarchical fitting strategy was used for image registration with a minimum step size of 2

mm [22].

Quantitative Analysis

A paired student t-test was employed to evaluate the group difference in MD and FA values

between the MCI participants and the controls for the entire region of the computed WM

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pathways of the cingulum. The local abnormalities of these WM fiber tracts were further

evaluated by performing a paired student t-tests along the geodesic paths in bi-directions

starting at the predefined ROI.

Results

Group Difference in FA Values

The mean diffusivity measures for the entire dorsal region of the computed cingulum bundles

for the amnestic MCI and control subject groups are listed in Table 1. For the entire computed

pathways, we found no significant difference in any diffusivity measure between the two

subject groups.

Table 1. Mean ( SD) values for MD (top) and FA measures (bottom) for computed WM

cingulum pathways for MCI and age-matched normal controls. The unit of MD is (× 10

±

-6

mm2/sec).

White matter tract Control MCI t-value p-value df MD (left cingulum) 766± 41 759± 44 0.73 0.47 32 MD (right cingulum) 796± 43 796± 41 0.65 0.52 32 FA (left cingulum) 0.43± 0.05 0.43± 0.06 -0.10 0.92 32 FA (right cingulum) 0.40± 0.04 0.40± 0.03 0.57 0.57 32

Left Cingulum

With the geodesic mapping, Figure 2 demonstrates the FA value degradations at the 95%

confidence level occurred at the location shown in green color. This degradation area is about

3.83mm long along the fiber bundles. The ROI size is 1.81*0.9*1.65mm.

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(a) (b) (c)

Figure 2 FA value degradations along the left cingulum tract in MCIs. (a) shows the left

cingulum bundle mask overlapped on the FA value indexed color map. The ROI is in blue

and is the starting point of the geodesic mapping. The green color illustrates the region which

shows significant FA value reduction in MCIs compared with the control subjects. (b)

illustrates the FA value distributions of the control and MCI groups along the geodesic paths.

(c) gives the p-value of the paired student t-test along the geodesic paths.

This analysis did not find significant MD value differences along the left cingulum. Figure 3

shows the MD value distributions and p-value along the geodesic path.

(a) (b)

Figure 3 Comparison of the MD values along the left cingulum. (a) illustrates the MD value

distributions of the control and MCI groups along the geodesic paths. (b) gives the p-value of

the paired student t-test along the geodesic paths.

Right Cingulum

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We did not find significant FA value differences in any area of the right cingulum. Figure 4

illustrates the right cingulum bundle mask overlapped on the FA value indexed color map and

the analysis results.

(a) (b) (c)

Figure 4 FA value distributions along the right cingulum. (a) shows the cingulum tract mask

overlapped on the FA value indexed color map. The ROI is in blue and is the starting point in

geodesic mapping. (b) illustrates the FA value distributions of the control and MCI groups

along the geodesic paths. (c) gives the p-value of the paired student t-test along the geodesic

paths.

The experiment did not find significant MD value differences along the right cingulum either.

Figure 5 shows the MD value distributions and p-value along the geodesic path.

Figure 5 Comparison of the MD values along the right cingulum. (a) illustrates the MD value

distributions of the control and MCI groups along the geodesic paths. (b) gives the p-value

after paired student t-test along the geodesic paths.

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Impact of Different ROI Size

To assess the possible effect caused by the size of ROIs, we implemented experiments with

two ROIs of different size. The FA value measurements of the small ROI with dimension

1.81*0.9*1.65mm and the large ROI with dimension 5.4*0.9*4.13mm are shown in Figure 1

and Figure 6 repectively. In Figure 6, the FA value degradation area in MCIs is about 2.67mm

in length along the geodesic path. The MD value significant difference at the 95% confidence

level was not found.

The comparison shows that ROIs of different size generate similar but not identical results.

To have a better understanding on how the aforementioned FA value degradations might be

affected by the size of the ROIs, we probed the voxels covered by the left cingulum bundle

mask (Figure 7) and compared their FA values according to the voxel indices in the two ROI

cases. A group of 17 connected voxels were extracted with significant FA value differences at

the 95% confidence level in both cases. The two groups contain the same set of voxels. They

are located in the same region where the aforementioned significant FA value degradations

were found. Furthermore, since the small ROI generated a thinner fiber bundle than that

generated by the large ROI, fewer number of fiber covered voxels were averaged within each

geodesic arc length in the small ROI than that in the large ROI case. With the same number

of voxels having significant FA value differences, the large ROI, subsequently the thick fiber

bundle, would blur the FA value reduction to some degree. This explains the observation that

the small ROI demonstrates a relatively longer FA value degradation region along the

geodesic path than that of the large ROI.

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(a) (b) (c) Figure 6 FA value degradations along the left cingulum in MCIs with ROI size

5.4*0.9*4.13mm. This degradation area is about 2.67mm along the fiber bundle. (a) shows

the cingulum bundle mask overlapped on the FA value indexed color map. The ROI is in blue

and is the starting point in geodesic mapping. The green color illustrates the region which has

significant FA value reduction in MCIs compared with control subjects. (b) illustrates the FA

value distributions of the control and MCI groups along the geodesic paths. (c) gives the

p-value after paired student t-test along the geodesic paths.

(a) (b) (c)

Figure 7 Fiber covered voxel based comparisons of the FA value. A group of 17 connected

voxels were found. (a) Fiber covered voxels overlapped on the FA value indexed color map.

Voxels with significant FA value reductions with at the 95% confidence level are in red. (b)

FA value distribution of the 17 connected voxels for both the control and MCI groups. (c)

p-value of voxels FA value difference after a paired student t-test.

Discussion

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Previous DTI studies in amnestic MCI have found significantly reduced measures of FA

value within posterior dorsal regions of the left cingulum bundles [6, 7, 8]. These studies

employed both ROI and automated VBM analyses. Although ROI analyses are robust in large

WM tracts, within thinner WM pathways it may be less reliable due to confounding partial

volume effects, exacerbating the difficulty associated with the accurate and consistent

placement of ROIs within target tracts across all subjects [9]. The VBM analysis method

reduces this problem, although issues concerning image registration, segmentation and the

choice of smoothing kernels prior to statistical analysis of grouped data are still to be resolved

[9]. The presence of unrelated fibers may also result in the contamination of targeted fiber

pathways using this approach. In contrast, DTI tractography enables robust generation of

fiber trajectories across subject groups with less off-target fiber contamination. In addition,

the integrity of the computed tracts can be determined by evaluating diffusivity indices either

averaged for the entire tract or along the length of the WM pathway in a spatially continuous

fashion [10, 20].

This is the first study to define the curved cingulum tracts using DTI tractography and to

exam the micro structural changes along the left and right cingula in amnestic MCIs.

Non-invasive neuroimaging techniques, which can investigate the integrity of the cingulum

fasciculi, are extremely important in understanding the progression of AD. There is

converging agreement based upon structural and metabolic studies of the importance of the

involvement of the posterior cingulate gyrus in AD [2,5,7,23,24]. It is important to study the

link between WM pathways of the cingulate gyrus and the cholinergic system [25]. With the

proposed technique, the entire curvilinear left and right cingulum regions were defined and

evaluated. The significantly reduced FA area localized to the left cingulum in the MCI

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participants is in agreement with the earlier ROI analyses [6]. We found no significant

difference in the diffusivity measure between the MCI participants and control subjects

averaged across the entire computed WM tract. The findings of this study reaffirm the

importance of being able to spatially define a complex 3D region of interest in DTI

tractography and to study the diffusion measures along the length of the WM pathways.

There are a number of limitations with this study. The term amnestic MCI applies to a

heterogeneous group of patients, thus it can be difficult to compare results from different

studies. However, our findings based on the use of DTI tractography and analyses of geodesic

paths are in agreement with those presented in previous studies [6, 7, 8]. Due to the

signal-to-noise limitations at the resolution of our DTI data, even with the use of an optimized

DTI acquisition scheme, we could not robustly compute WM trajectories for the more ventral

pathway of the cingulum bundles. Analysis of geodesic paths of the WM tracts that project

from the hippocampus to the posterior cingulate gyrus would be extremely useful and

provides a challenge for high field (>3T) DTI studies in AD. Although DTI-based

tractography method is automated, tractography algorithms normally rely on the manual

placement of ROI to compute target WM trajectories. In this study, we carefully placed the

ROI within the cingulum with the help of an FA indexed color map. Alternative methods of

analyzing diffusivity measures along target WM trajectories that do not require accurate

within subject registration would be of considerable benefit [10]. Inclusion of a reference AD

subject group would have been of use to explore the full potential of this new fiber tract

analysis technique.

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Conclusion

Using DTI-based tractography, we defined the whole curved cingulum pathways. Combined

with geodesic mapping, we measured local micro structural WM changes along the two

cingula in MCI participants compared to control subjects. Significant reduction in the FA

value within specific anatomical regions was only detected by evaluating diffusivity

measures mapped as geodesic paths. Our analysis technique is promising and may provide a

more sensitive technique for determining the integrity of WM tracts in the brain.

Acknowledgements

The authors would like to thank Greig de Zubicaray and Brona O'Dowd for their work on the

MCI project. The research work of J. Zhang was supported in part by the US National Science

Foundation under grant CCF-0527967 and CCF-0727600, in part by the National Institutes of

Health under grant 1R01HL086644-01, in part by the Kentucky Science and Engineering

Foundation under grant KSEF-148-502-06-186, and in part by the Alzheimer’s Association

under grant NIRG-06-25460.

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